Market Price Volatility Research Articles

Measuring Rice Price Volatility and Its Determinants in Tanzania: An Implication for Price Stabilization Policies

High price volatility in agricultural food markets has a greater impact not only on smallholder farmers but also can affect the incomes and purchasing power of a substantial proportion of the Tanzanian population and decrease food security, especially to the lower middle class. This study applies the ARCH-GARCH and the VAR/VECM models to examine the dynamics and factors influencing price volatility in the domestic rice market. The results of the price volatility analysis show that the volatility of rice prices tends to be low and persistent over the long run. This is supported by the estimation results of factors affecting price volatility, which showed that supply variables play an important role in the short and long run in influencing rice price volatility. The prices in the producing regions (large surplus areas) turned out to be more volatile than the prices in the main consuming regions (large deficit areas). This means that producers are exposed to a much higher price risk than consumers. Thus, a favorable marketing environment for traders and farmers, transparent trade policies, reliable market information, and organized market infrastructure are essential to reduce food price volatility which has a wider impact on economic growth.

An empirical study on effect of financial accounting indicators towards stock market price volatility

An empirical study on effect of financial accounting indicators towards stock market price volatility

Price Risk Control of Natural Resource Commodities through Behavioral Finance Analysis: An Information Transfer Perspective

To fully understand the market price volatility mechanism of natural resource commodities (NRCs), and control the price risks of NRCs, it is important to deeply analyze how NRC price is affected by uncertain risk factors, such as supply risk, demand risk, macroscopic price risk, political price risk, policy price risk, seasonal price risk, and sudden price risks. The theory of behavioral finance can establish a transaction decision‐making model more in line with the actual market situation. Therefore, this paper explores the price risk control of NRCs from the perspective of financial theories. Firstly, the authors empirically examined the specific impacts of uncertain risk factors on NRC price, and the directions of the impacts. Next, the price volatility and transaction risks of NRCs brought by information transmission were analyzed, following by the construction of an information transmission model for NRC trading market. After that, a dynamic price model was built for NRCs based on the theory of behavioral finance. Finally, the effectiveness of the proposed model was verified through experiments.

Developing a long-lasting offshore wind business case towards a Dutch decarbonised energy system by 2050

The integration of large-scale offshore wind power in the energy system will have a major effect on electricity markets. It may lead to large market price volatility due to the inherent variability of wind energy in terms of power fluctuations, forecast errors and insufficient flexibility on the demand side. This study models future business cases for offshore wind farms in two reference national scenarios for the Netherlands, namely NECP2030 and TRANSFORM. Results show that the value of offshore wind in 2030, according to NECP scenario is 39.9 €/MWh, and that electricity price in the TRANSFORM scenario, which considers aggressive development towards a sustainable economy, is a high 104 €/MWh by 2050. To consider ways of improving the return on investment for offshore wind farms in future markets, an optimisation problem is defined, where the wind farm has the choice to either sell the generated electricity to the spot market or to an electrolyser. Results show a potential advantage in using an electrolyser to produce green hydrogen for offshore wind farms, with net profit of 41.4 M€, compared to when offshore wind farms sell electricity solely to the spot market, where the profits are 36 M€.

The Impact of Real Manipulation and Tax Management on Future Market Value: An Artificial Intelligence Simulation of High Earnings Quality

Providing empirical proof of the negative impact of manipulation activity pushed management to adhere to the available regulation by publishing high financial reporting quality. This one has a significant effect negatively on a volatile market price movement because of illustrates the actual earnings. It is not an obstacle for the investor in predicting the future return with high accuracy when there is a minimum chance for the opportunity behavior. This causal research has developed a new variable to measure the investor's perception, and it is the future market value as a proxy for future return. The observation data used the samples on the listed company in the industrial manufacturing sector from 2015 until 2020, which amounted to 384 observations. The management's effort to deduct the manipulation activity can be interpreted as the minimum level of misleading information. When the investor has no tolerance for manipulation activity, the management should be "prudent" in designing the accounting treatment policy to illustrate real earnings. It is a sign of high probability in reaching out to the better prospect, proving the interactive feedback between management and investor through the Decision Tree Model and Bayes Theorem. This research has adopted the maximum simplex models as an Artificial Intelligence simulation for maximizing each party's maximum utility as implication game theory, like investors and management in making their strategic decisions. Principally, the regulator should force management to level up the quality of financial reporting because of no tolerance for any infringement on the legal regulations.

Does the Launch of Shanghai Crude Oil Futures Stabilize the Spot Market? A Financial Cycle Perspective

Based on the examination of price discovery between Shanghai crude oil futures and the spot market, this paper explores whether the introduction of Shanghai crude oil futures can play a stabilizing role in the spot market, alleviating the impact of the financial cycle risk on the crude oil market from March 2018 to December 2019. The results show that there is only a uni-directional relationship of the spot price to futures price, and spot plays a leading role in price discovery. The risk of the financial cycle will increase the volatility of spot price, and the introduction of crude oil futures market can increase the impact of the financial cycle on the spot market. The additional research on the microcosmic mechanism of Shanghai crude oil futures indicates that crude oil futures market mainly influences the spot market fluctuation through the behaviour of traders: speculation increases price volatility in the spot market, which is more pronounced in the high volatility of the financial cycle as oppose to hedging transaction.

Trading fast and slow: The role of deliberation in experimental financial markets

Financial bubbles cause misallocation of resources and even systemic crises. Experimental finance has long studied both the determinants of bubbles and institutional measures to prevent them. Within the framework of the dual-process theory, we experimentally investigate whether traders under higher time pressure (Fast condition) behave differently than traders under lower time pressure (Slow condition). Relative to the Fast condition, the Slow condition dampens market price volatility, dramatically reduces the spread between ask and bid limit orders, and leads to higher equality in payoffs.

Determinants of Commodity Futures Prices: Decomposition Approach

Developing models to analyze time series is a very sophisticated, time-consuming, but interesting experience for researchers. Commodity price component determination is challenging due to remarkable price volatility, uncertainty, and complexity in the futures market. This study aims to determine the components that drive the market price of commodity futures. This study utilized the decomposition methods, empirical mode decomposition (EMD), and variational mode decomposition (VMD), to analyze three commodity futures prices data: corn from agricultural products, crude oil from energy, and gold from industrial metal. We applied these techniques to decompose the daily data of each commodity price from different periods and frequencies into individual intrinsic mode functions for EMD and modes for VMD. We used the hierarchical clustering method and Euclidean distance approach to classify the IMFs and modes into high-frequency, low-frequency, and trend. Next, applying statistical measures, particularly, the Pearson product-moment correlation coefficient, Kendall rank correlation, and Spearman rank correlation coefficient, we observed that the trend and low-frequency parts of the market price are the main drivers of commodity futures markets’ price fluctuations. The low-frequencies are caused by special events. In a nutshell, commodity futures prices are affected by economic development rather than short-lived market variations caused by ordinary disequilibrium of supply-demand.

A predictive maintenance policy considering the market price volatility for deteriorating systems

In reality, under the impacts of market dynamism and uncertainty, various input costs of maintenance optimization programs such as spare part cost strongly fluctuate over time. This paper aims at introducing the market price volatility (fluctuation) into the predictive maintenance optimization framework. To this end, we first adopt a Cox-Ingersoll-Ross (CIR) process to describe the evolution of interest rates and a log-diffusion process to model fluctuating maintenance costs. An adapted predictive maintenance policy is then proposed. According to the policy, maintenance decisions are made based on the predictive information about both the system health state and the price volatility level. The consideration of price volatility helps to reduce the negative impacts of the cost fluctuation on the maintenance decision-making, but it makes the evaluation of maintenance performance more complex. To overcome this issue, an analytical solution is developed based on the semi-regenerative properties of the maintained system. Finally, different theoretical and numerical studies confirm the necessity of taking into account the price volatility and the effectiveness of the proposed policy.

Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market

The close interaction between the electricity market and the end-users can assist the demand response (DR) aggregator in handling and managing various uncertain parameters simultaneously to reduce their effect on the aggregator's operation. As the DR aggregator's main responsibility is to aggregate the obtained DR from individual consumers and trade it into the wholesale market. Another responsibility of the aggregator is proposing the DR programs (DRPs) to the end-users. This article proposes a model to handle these uncertainties through the development of a novel hybrid stochastic-robust optimization approach that incorporates the uncertainties around wholesale market prices and the participation rate of consumers. The behavior of the consumers engaging in DRPs is addressed through stochastic programming. Additionally, the volatility of the electricity market prices is modeled through a robust optimization method. Two DRPs are considered in this model to include both time-based and incentive-based DRPs, i.e., time-of-use and incentive-based DR program to study three sectors of consumers, namely industrial, commercial, and residential consumers. An energy storage system is also assumed to be operated by the aggregator to maximize its profit. The proposed mixed-integer linear hybrid stochastic-robust model improves the evaluation of DR aggregator's scheduling for the probable worst-case scenario. Finally, to demonstrate the effectiveness of the proposed approach, the model is thoroughly simulated in a real case study.

АКТУАЛЬНІ ПРОБЛЕМИ ГЛОБАЛІЗАЦІЇ ФОНДОВИХ РИНКІВ З ПОЗИЦІЇ ІНСТИТУЦІОНАЛІЗМУ

The problems of stock markets globalization using theoretical approaches and institutionalism tools have been investigated. The following problems have been identified: unlimited volume of stock information, which complicates the decision-making process; the possibility of including local stock institutions in global trading networks; the impact of transaction costs on the volatility of market prices for financial instruments; limited access of small and medium-sized businesses to global stock markets. It has been proved that the institutionalism tools and the network approach make it possible to form a more realistic architecture of the global stock market, to define and comprehensively analyze the relationship between elements of the traditional infrastructure.

An Investor’s Investment Plan with Stochastic Interest Rate under the CEV Model and the Ornstein-Uhlenbeck Process

The aim of this paper is to maximize an investor’s terminal wealth which exhibits constant relative risk aversion (CRRA). Considering the fluctuating nature of the stock market price, it is imperative for investors to study and develop an effective investment plan that considers the volatility of the stock market price and the fluctuation in interest rate. To achieve this, the optimal investment plan for an investor with logarithm utility under constant elasticity of variance (CEV) model in the presence of stochastic interest rate is considered. Also, a portfolio with one risk free asset and two risky assets is considered where the risk free interest rate follows the Ornstein-Uhlenbeck (O-U) process and the two risky assets follow the CEV process. Using the Legendre transformation and dual theory with asymptotic expansion technique, closed form solutions of the optimal investment plans are obtained. Furthermore, the impacts of some sensitive parameters on the optimal investment plans are analyzed numerically. We observed that the optimal investment plan for the three assets give a fluctuation effect, showing that the investor’s behaviour in his investment pattern changes at different time intervals due to some information available in the financial market such as the fluctuations in the risk free interest rate occasioned by the O-U process, appreciation rates of the risky assets prices and the volatility of the stock market price due to changes in the elasticity parameters. Also, the optimal investment plans for the risky assets are directly proportional to the elasticity parameters and inversely proportional to the risk free interest rate and does not depend on the risk averse coefficient.

Price transmission and supply response: the case of Indian small cardamom

Market price volatility, the major challenge faced by the cardamom exporters greatly hinders the investment and destabilizes the earning of small holders. The present study attempted to analyse the price transmission between Indian and international markets and study the supply response of small cardamom to changes in price. The co-movement of prices of small cardamom exist between the Indian and international markets after trade liberalisation and the price transmission has been from the international market to the Indian market. The short-run disequilibrium has been found between the Indian and international prices of cardamom, which got corrected with varying speed of adjustment. The positive and significant elasticity of supply of small cardamom with respect to its own two year lagged price has been established. Crop specific price stabilization mechanism would help to overcome the wide fluctuations in prices of small cardamom.

Unlearned lessons of food price spikes

The article substantiates the author’s hypothesis of the fundamental reasons for periodic «ups» in prices for essential food products, including the most recent price jump in the second half of 2020. Both the official assessments of the causes of recurring food price surges and the measures taken by the executive branch to stop and prevent them are subjected to critical analysis. Conclusions and fundamental proposals are formulated aimed at eradicating the systemic causes of price volatility in the domestic food market.

A review on powertrain subsystems and charging technology in battery electric vehicles: Current and future trends

The transport industry is a major contributor to both local pollution and greenhouse gas emissions (GHGs). The key challenge today is to mitigate the adverse impacts on the environment caused by road transportation. The volatile market prices and diminishing supplies of fuel have led to an unprecedented interest in battery electric vehicles (BEVs). In addition, improvements in motor efficiencies and significant advances in battery technology have made it easier for BEVs to compete with internal combustion engine (ICE) vehicles. This paper describes and assesses the latest technologies in different elements of the BEV: powertrain architectures, propulsion and regeneration systems, energy storage systems and charging techniques. The current and future trends of these technologies have been reviewed in detail. Finally, the key issue of electric vehicle component recycling (battery, motor and power electronics) has been discussed. Global emission regulations are pushing the industry towards zero or ultra-low emission vehicles. Thus, by 2025, most cars must have a considerable level of powertrain electrification. As the market share of electric vehicles increases, clear trends have emerged in the development of powertrain systems. However, some significant barriers must be overcome before appreciable market penetration can be achieved. The objective of the current study is to review and provide a complete picture of the current BEV technology and a framework to assist future research in the sector.

WORLD OIL PRICE SHOCKS IN MACROECONOMIC ASEAN +3 COUNTRIES: MEASUREMENT OF RISK MANAGEMENT AND DECISION-MAKING A LINEAR DYNAMIC PANEL APPROACH

The increase in oil prices in the 1970s has had a quite significant impact over the decades since the rise in inflation has had an impact on hyperinflation, recession, lowered productivity and economic growth. The World Bank (2021) forecasts that oil prices will exceed US$44 per barrel in 2021 and US$50 per barrel in 2022, while several factors affect the World Bank's projections, including the persistence of economic issues in the coming years. The purpose of this paper was to empirically assess the impact of oil prices on ASEAN+3 inflation and economic growth. The framework that can be applied to linear dynamic panel data to achieve this goal is the First Difference-Generalized Moment Method (FD-GMM) estimator method. This study used panel data representing ASEAN+3 countries and annual data over the period 2011-2020. The findings of the study indicated that, over the period, increasing oil prices were associated with higher inflation, and higher economic growth in ASEAN+3. Another result was that higher inflation is related to lower economic growth. Lower and higher economic growth was related to decreased inflation. High inflation creates high costs of economic development and social prosperity, therefore that policymakers are expected to adopt policies that are not only good for the short term, but also good for the long term to establish long-term prosperity and long-term price stability. In addition, a variety of non-economic variables that affect global market price volatility should also be considered to reduce potential market risks.Keywords: oil price shock, inflation, Production Growth, economic development, econometricsJEL Classifications: E31, E42, E63, F43, F62DOI: https://doi.org/10.32479/ijeep.11249

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

The limitedness of the nonrenewable local energy resources in Israel, even in the background of the later gas fields’ findings, continues to force the state to devote various efforts towards ‘green’ energy development. These efforts include installations, both for the solar and for wind energy, thus improving the diversity of energy sources. While the standard discounted cash flow (DCF) method using the net present value (NPV) criterion is extensively adopted to evaluate investments, the standard DCF method is inappropriate for the rapidly changing investment climate and for the managerial flexibility in investment decisions. In recent years, the real options analysis (ROA) technique has been widely applied in many studies for the valuation of renewable energy investment projects. Taking into account the above background, we apply, in this study, the real options analysis approach for the valuation of wind energy turbines and apply it to the analysis of wind energy economic potential in Israel, which is the context of our work. We hypothesize that due to nature of wind energy production uncertainties, the ROA method is better than the alternative. The novelty of this paper includes the following: real world wind statistics of the Merom Golan site in Israel (velocity 3.73 m/s, with a standard deviation of 2.03 m/s), a realistic power generation estimation (power generation of 1205.84 kW with a standard deviation of about 0.5% in annual value which is worth about 1.3 M$ per annum), and an economic model to evaluate the profitability of such a project. We thus discuss the existing challenges of diversifying renewable energy sources in Israel by adding wind installations. Our motivation is to introduce a method which will allow investors and officials to take into account uncertainties when deciding in investing in such wind installations. The outcomes of the paper, which are obtained using the method of Weibull statistics and the Black–Scholes ROA technique, include the result that market price volatility adds to the uncertainties much more than any wind fluctuations, provided that the analysis is integrated over a long enough time.

Evidenciação do Contexto Econômico na Relação entre Governança Corporativa e Volatilidade das Ações nas Companhias Abertas Brasileiras

Objetivo : analisar que forma o contexto econômico afeta a relação entre a governança corporativa e a volatilidade das ações das ações das companhias abertas brasileiras listadas no B3 SA - Brasil, Bolsa, Balcão (B3), período de 2010 a 2018.Método : partindo-se de uma pesquisa quantitativa, descritiva e documental, utilizando a volatilidade das ações em base anual como métrica para volatilidade (variável dependente); mecanismos internos (estrutura de propriedade e controle, número de membros do conselho administrativo e fiscal) e mecanismos externos (níveis de governança da B3, American Depositary Receipt e free float ) como proxies de governança corporativa (variável independente de interesse); e variáveis de controle (Produto Interno Bruto - PIB e outras).Originalidade / Relevância : não há consenso em relação à forma que as práticas de governança corporativa afetam a volatilidade das ações, ao se considerar o contexto econômico em que o país se encontra, visto que diferentes proxies podem causar efeitos diversos perante o mercado (Li et al ., 2013; Litov et al ., 2006).Resultados : verificou-se que, de modo geral, os dispositivos adaptam-se com relação à volatilidade das ações apenas quando apareceu em conjunto com a variação do PIB. Já os mecanismos externos não compensam em relação à volatilidade das ações.Contribuições Teóricas/Metodológicas: amplia-se a discussão a respeito da interação das práticas de governança corporativa com a volatilidade dos preços das ações das companhias brasileiras, assim como os diferentes enfoques da tomada de decisão ao se analisar os mecanismos internos e externos de governança corporativa no contexto econômico brasileiro.

A Study on the Optimal Market Value and Price Volatility in the Housing Market

The optimal market value of a private house consists of intrinsic value and bubbles. It has characteristics that change over time and will be stable over the long term. Assuming that the optimal value is a rental function, the nature of the optimal value can be analyzed through research on the factors and variability of the real price considering the consumer price index. First, The factors of real estate change were estimated in consideration of real estate rent, demographic aspects and variables, unemployment, income variables, real estate consumer sentiment, monetary policy and real estate policies. Second, the effectiveness and volatility of monetary and real estate policies were analyzed based on the relevance of the sale price and the chunsei price. The cost of housing services should be viewed in conjunction with a value perspective, rather than simply a cost-based approach of rising housing costs. and What the study suggests is that it understands the process of value changes in the housing market and hopes that research on causes and characteristics will help policy.

Renewable On-Site Power Generation for Manufacturing Companies—Technologies, Modeling, and Dimensioning

The expansion of renewable energies and the concomitant compensatory measures, such as the expansion of the electricity grid, the installation of energy storage facilities, or the flexibilization of demand, lead to a more elaborated energy supply system. Furthermore, the technological development of small power plants has further progressed, and many novel technologies have achieved grid parity. For manufacturing companies, the integration of renewable generation plants at their own site therefore represents a promising strategy for being both technically independent of the electricity grid and autonomous of price policy decisions and volatile market prices. This paper outlines the existing decentralized, renewable power generation technologies, their energetic modeling, and a hybrid optimization methodology for their dimensioning that uses mixed integer linear programming (MILP) and linear programming (LP) problem formulation. Finally, the introduced dimensioning method is applied to an exemplary manufacturing company that is assumed to be in the central part of Germany and located in the metalworking sector. The company has an electricity demand of approximately 20,000 MWh/a. The optimization results in a maximum expansion of PV and the use of CHP to cover the base load leading to a promising energy cost reduction of almost 20%.